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Thread: 2019 Off-Season Thread: We Got This Bread, Man

  1. #801
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    I wish Hockey Central was longer than an hour. I know its not a summer thing but while we're talking about NHLN that's what I'd like to see.

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    Less than a month till the first pre-season game!!!!
    Training camp opens up in like 3 1/2 weeks.

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    Not soon enough

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    Pictures are flooding in. The boys are back in town, baby! Hockey is almost here!

    I plan on acting as if Traverse City is the Stanley Cup Final.
    GORTON 2020

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    Quote Originally Posted by ThirtyONE View Post
    Pictures are flooding in. The boys are back in town, baby! Hockey is almost here!

    I plan on acting as if Traverse City is the Stanley Cup Final.
    my palm is raw
    Lias Andersson for #AJT2019

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    Quote Originally Posted by josh View Post
    my palm is raw
    Is this some kind of a sex joke?

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    Hot chicks thread
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    Let's Go Rangers!

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    The Athletic's Rangers season preview: https://theathletic.com/1167323/2019...-york-rangers/

    Projected points: 84.9
    Chance of making the 1st round of the playoffs: 13%

    Tl;dr
    - Quite a bit of uncertainty regarding how the rookies/young players will perform. Could see a significant upswing if a couple (Chytil, Andersson, Kravtsov, Fox etc) hit the ground running.
    - The projected first line (Panarin, Zib, Kakko) is excellent
    - The rest of the forward lines not so much. Bottom 9 is substandard, bottom 6 is dreadful
    - Howden is one of the worst defensive players in the league apparently
    - The Rangers are very weak down the middle. Although this makes the assumption that Chytil, Andersson and Howden are the 2, 3 and 4C's.
    - The Rangers D is the teams biggest weakness, even after adding Trouba
    - Goaltending is a strength, largely because of Georgiev. Make of that what you will
    - Despite the above, this a team with tremendous upside
    Last edited by Gravesy; 09-04-2019 at 04:22 AM.

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    Quote Originally Posted by Gravesy View Post
    The Athletic's Rangers season preview: https://theathletic.com/1167323/2019...-york-rangers/

    Projected points: 84.9
    Chance of making the 1st round of the playoffs: 13%

    Tl;dr
    - Quite a bit of uncertainty regarding how the rookies/young players will perform. Could see a significant upswing if a couple (Chytil, Andersson, Kravtsov, Fox etc) hit the ground running.
    - The projected first line (Panarin, Zib, Kakko) is excellent
    - The rest of the forward lines not so much. Bottom 9 is substandard, bottom 6 is dreadful
    - Howden is one of the worst defensive players in the league apparently
    - The Rangers are very weak down the middle. Although this makes the assumption that Chytil, Andersson and Howden are the 2, 3 and 4C's.
    - The Rangers D is the teams biggest weakness, even after adding Trouba
    - Goaltending is a strength, largely because of Georgiev. Make of that what you will
    - Despite the above, this a team with tremendous upside
    I feel like articles like this assume no progress by any young player from last year to this year.

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    Quote Originally Posted by Pete View Post
    I feel like articles like this assume no progress by any young player from last year to this year.
    What the Rangers have going for them in beating this projection and taking a major leap is the optimism that comes with their youth movement. The team has a number of young players who are either coming in as rookies or struggled in their first taste of NHL action last season, creating more uncertainty than usual. Big steps are not out of the question and could propel this team forward more than expected, but that’s still a very tall task — hence their projected position here.
    The projections are entirely at the player level and are based on an all-in-one stat I created a little over a year ago called Game Score. It combines all the basic box score stats into one number to measure a player’s value. As one season isn’t really enough to get a good read on a player, I use the last three seasons instead. The seasons were weighted by recency using a multi-variate regression and the results of that are regressed to the mean based on the repeatability of each component and the size of each player’s sample. There’s also an age adjustment as we expect players to get better as they move towards their prime and worse as they move away from it.
    I think you're right, for the most part. They almost certainly err massively on the side of caution when projecting improvement in young players.

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    Quote Originally Posted by Gravesy View Post
    I think you're right, for the most part. They almost certainly err massively on the side of caution when projecting improvement in young players.
    ... off a self admitted made up stat...

    Where do they get these people?

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    From the same place we get our politicians - twitter.
    Lias Andersson for #AJT2019

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    Quote Originally Posted by Pete View Post
    I feel like articles like this assume no progress by any young player from last year to this year.
    that was my exact thought.. These previews are well researched and the metrics are very well presented.. but they really don't consider improvements (or regression). With a team counting on youth, the expectation is there will be growing pains, but some of these kids are going to continue to grow.

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    Quote Originally Posted by Pete View Post
    ... off a self admitted made up stat...

    Where do they get these people?
    This is Dom Luszczyszyn, who, aside from having a really, really hard name to spell, has a history as a hockey reporter with THN and tends to write from an analytics/data perspective because it's kind of his jam. Using three seasons worth of weighted data in a multivariate regression to project next season is a reasonable model structure - it's a similar projection model as would be used in many businesses to help figure out how many folks you'd need to hire to meet customer demands, for example.

    Obviously, most models place a premium on having a history, so when we're talking about a team where there is little history (we're likely to ice something like 11 players with fewer than 100 games NHL experience), the projection gets murkier. And just to get ahead of the "oh well then its a bad model" crowd, no decent data scientist is going to make shit up and find "expected comparables" or any of that crap just to make their model function "better". They're going to project based off the best data they have - so, for example, based off Liiga data, what values seem to work well for translating Liiga to NHL, and the history of 2nd overall picks, he's got Kakko at 51 points and 1.4 WAR, and calls it murky because he's not got the data to call it concrete.

    He owns a lot of his logic in the article, too:

    Some might question the Rangersí true talent level being lower than the teamís already low 78-point finish, but whatís vital to remember is how barren the team was after last yearís trade deadline. Before shipping off Mats Zuccarello and Kevin Hayes (worth nearly a combined four wins), the Rangers were 27-26-8 on the season, an 83-point pace. After, the team went 5-10-5, a 62-point pace. Small sample size, but itís that latter team the new additions are being added to, an important consideration to make when predicting the teamís immediate future. The terrific offseason looks great in a vacuum, but the value added is more marginal once last seasonís deadline deals are accounted for.

    Itís also tougher to make the playoffs in the East due to the extra team, and itís even harder now with the balance of power shifting in that direction, as we saw last season with the eighth seed finishing with 98 points in the East and 90 points in the West. This season, the top eight teams in the East have an average point projection of 100 points, while in the West itís 97. Thatís a tough hill to climb for New York, as itís hard to make an argument for the Rangers against most of the teams above them.

    What the Rangers have going for them in beating this projection and taking a major leap is the optimism that comes with their youth movement. The team has a number of young players who are either coming in as rookies or struggled in their first taste of NHL action last season, creating more uncertainty than usual. Big steps are not out of the question and could propel this team forward more than expected, but thatís still a very tall task ó hence their projected position here.
    I don't know if any of you actually subscribe to the Athletic (and if you don't....really? It's worth every goddamn penny especially with their crazy 50-60% off promos), but generally speaking, he's not only addressed these criticisms in the article, he's recognized all of it as possible and how it might impact his work.
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    Quote Originally Posted by G1000 View Post
    This is Dom Luszczyszyn, who, aside from having a really, really hard name to spell, has a history as a hockey reporter with THN and tends to write from an analytics/data perspective because it's kind of his jam. Using three seasons worth of weighted data in a multivariate regression to project next season is a reasonable model structure - it's a similar projection model as would be used in many businesses to help figure out how many folks you'd need to hire to meet customer demands, for example.

    Obviously, most models place a premium on having a history, so when we're talking about a team where there is little history (we're likely to ice something like 11 players with fewer than 100 games NHL experience), the projection gets murkier. And just to get ahead of the "oh well then its a bad model" crowd, no decent data scientist is going to make shit up and find "expected comparables" or any of that crap just to make their model function "better". They're going to project based off the best data they have - so, for example, based off Liiga data, what values seem to work well for translating Liiga to NHL, and the history of 2nd overall picks, he's got Kakko at 51 points and 1.4 WAR, and calls it murky because he's not got the data to call it concrete.

    He owns a lot of his logic in the article, too:



    I don't know if any of you actually subscribe to the Athletic (and if you don't....really? It's worth every goddamn penny especially with their crazy 50-60% off promos), but generally speaking, he's not only addressed these criticisms in the article, he's recognized all of it as possible and how it might impact his work.
    No model is a good model if it doesn't work across the board. Might as well use EA ratings.

    WAR has no place in hockey. It's a fantasy baseball stat, and baseball is way less of a "team" sport than hockey is.

    This is what happens when you try to make a make sports purely formulaic and put math behind things where math isn't the answer and there are all kinds of flaws with the logic.

    I don't subscribe to the athletic because I see shit like this posted and it's pure trash.

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    Quote Originally Posted by Pete View Post
    No model is a good model if it doesn't work across the board. Might as well use EA ratings.

    WAR has no place in hockey. It's a fantasy baseball stat, and baseball is way less of a "team" sport than hockey is.
    We've been through this. Models aren't perfect. They're not supposed to be. I don't feel the need to repeat myself on this one. If you're looking for a perfect model before buying into one, you'll be waiting a real long time.

    As for WAR in hockey - oof, that's an antiquated stance. Sabermetrics worked. They worked well. They worked so well that literally every other sport adopted them and adapted them to their respective sports. Football's got them. Soccer has them. Basketball absolutely has them. Arguing that WAR or stats like it have no place in hockey is like captaining a sailboat into a tsunami. You're on the wrong side of the water.

    This is what happens when you try to make a make sports purely formulaic and put math behind things where math isn't the answer and there are all kinds of flaws with the logic.

    I don't subscribe to the athletic because I see shit like this posted and it's pure trash.
    It's why you don't exclusively use math. Math can tell most of the story, but it still very much requires human intervention to explain anomalies. Math can't yet account for things like "hey, this player is a wildcard because we don't have data on him to project it right" or projected growth. As Luszczyszyn said in his piece.
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    Quote Originally Posted by G1000 View Post
    We've been through this. Models aren't perfect. They're not supposed to be. I don't feel the need to repeat myself on this one. If you're looking for a perfect model before buying into one, you'll be waiting a real long time.

    As for WAR in hockey - oof, that's an antiquated stance. Sabermetrics worked. They worked well. They worked so well that literally every other sport adopted them and adapted them to their respective sports. Football's got them. Soccer has them. Basketball absolutely has them. Arguing that WAR or stats like it have no place in hockey is like captaining a sailboat into a tsunami. You're on the wrong side of the water.


    I'd wager there's about a third of the league the model doesn't apply to. If that's good enough for you, great. I don't have to live by your standards. If you're basing an entire article on a formula you made up from thin air, it better be more reliable.

    Sabermetrics works for baseball, which is an individual team sport. It relies very little on things like chemistry the way hockey does.

    I don't really care what any other sport has or doesn't have. I also don't really care to deal with your arrogant commentary on it.
    Last edited by Pete; 09-05-2019 at 12:36 PM.

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    Quote Originally Posted by Flynn View Post
    that was my exact thought.. These previews are well researched and the metrics are very well presented.. but they really don't consider improvements (or regression). With a team counting on youth, the expectation is there will be growing pains, but some of these kids are going to continue to grow.
    Age and development are factors, and his model is based on standard data.

    What goes into those projections?
    The projections are entirely at the player level and are based on an all-in-one stat I created a little over a year ago called Game Score. It combines all the basic box score stats into one number to measure a player’s value. As one season isn’t really enough to get a good read on a player, I use the last three seasons instead. The seasons were weighted by recency using a multi-variate regression and the results of that are regressed to the mean based on the repeatability of each component and the size of each player’s sample. There’s also an age adjustment as we expect players to get better as they move towards their prime and worse as they move away from it. Lastly, there’s a small adjustment for usage.
    Nitpicking his methodology is fine (for instance, you could think his weighting in Game Score is off), but I think there's a little bit of forest/trees here. I mean, is a projection of the Rangers at 85 points really so unrealistic as to question the model? The rankings he's released have teams finishing:

    31 - OTT 71
    30 - DET 74
    29 - LAK 79
    28 - BUF 80
    27 - EDM 83
    26 - NYR 85
    25 - VAN 85
    24 - ARZ 85
    23 - CHI 87

    Wouldn't that ranking be basically the same if you're using just the eye test?

    https://theathletic.com/1166232/2019...ason-previews/

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    Well, no, Arizona is way too low because it's partially based on a year where they were crazy hurt...Hence the reason his made up stat is based on flawed thinking.

    Also, when he says "I adjust for X, Y, Z"...Adjusted how much? According to who? It half math, half made up. Might as well just say it's what he thinks and try to leave the [fake] numbers out of it.

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    Quote Originally Posted by Pete View Post
    I'd wager there's about a third of the league the model doesn't apply to. If that's good enough for you, great. I don't have to live by your standards. If you're basing an entire article on a formula you made up from thin air, it better be more reliable.
    The point of a model is to project what probably will happen - not what will happen. There's a difference. I'm not going to sit here and tell you the Rangers will have exactly 84 points, but the odds are that they will finish last or second last in the division, probably not by much. There's a series of outcomes - around 16% of simulations - where they're a playoff team, including a small chance they actually win the division.

    If you're playing blackjack and the dealer is showing an Ace, you're probably going to lose. You CAN win - you can beat the odds - but the most likely outcome is that you lose.

    It doesn't matter in the end; Dom's model is one of the better models out there, it's constantly being tweaked and tinkered with to remove as much error and imperfection as possible, and is certainly one of the more interesting takes on how to view the game.

    Sabermetrics works for baseball, which is an individual team sport. It relies very little on things like chemistry the way hockey does.
    While almost any advanced stat won't directly take into account chemistry, those who play with better players likely have higher outcomes values. Almost any combination stat would weight, say, a primary assist higher than a secondary assist. That probably helps Nick Backstrom, but hurts your outlet pass defenders who pile up those secondaries.

    Basketball having these stats kind of hits hard against your point though. While perhaps a more individual sport than hockey, it's similarly paced, reliant on chemistry, has similar variables and projection challenges, etc.

    I don't really care what any other sport has or doesn't have. I also don't really care to deal with your arrogant commentary on it.
    I can't make you care about it. Regardless, this wave of advanced analytics, hockeys version of sabermetrics, and the propensity toward using these models to identify good fits in personnel decisionmaking and long term planning is well underway and has been well documented. It's happening, and each year the models being produced by front offices, journalists, dedicated fans, and so on are getting better and better at explaining the nuances of the sport. Whether you choose to care or not is your call, but pretending it's not relevant to the game or the decisions made by folks close to it is equally wrong.
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